Combining gene ontology with deep neural networks to enhance the clustering of single cell RNA-Seq data.
Journal:
BMC bioinformatics
Published Date:
Jun 10, 2019
Abstract
BACKGROUND: Single cell RNA sequencing (scRNA-seq) is applied to assay the individual transcriptomes of large numbers of cells. The gene expression at single-cell level provides an opportunity for better understanding of cell function and new discoveries in biomedical areas. To ensure that the single-cell based gene expression data are interpreted appropriately, it is crucial to develop new computational methods.